Abstract: The size, complexity and number of databases used
for protein information have caused bioinformatics to lag behind in
adapting to the need to handle this distributed information.
Integrating all the information from different databases into one
database is a challenging problem. Our main research is to develop a
tool which can be used to access and manipulate protein information
from difference databases. In our approach, we have integrated
difference databases such as Swiss-prot, PDB, Interpro, and EMBL
and transformed these databases in flat file format into relational
form using XML and Bioperl. As a result, we showed this tool can
search different sizes of protein information stored in relational
database and the result can be retrieved faster compared to flat file
database. A web based user interface is provided to allow user to
access or search for protein information in the local database.
Abstract: This paper presents the experimental results on
artificial ageing test of 22 kV XLPE cable for distribution system
application in Thailand. XLPE insulating material of 22 kV cable
was sliced to 60-70 μm in thick and was subjected to ac high voltage
at 23
Ôùª
C, 60
Ôùª
C and 75
Ôùª
C. Testing voltage was constantly applied to
the specimen until breakdown. Breakdown voltage and time to
breakdown were used to evaluate life time of insulating material.
Furthermore, the physical model by J. P. Crine for predicts life time
of XLPE insulating material was adopted as life time model and was
calculated in order to compare the experimental results. Acceptable
life time results were obtained from Crine-s model comparing with
the experimental result. In addition, fourier transform infrared
spectroscopy (FTIR) for chemical analysis and scanning electron
microscope (SEM) for physical analysis were conducted on tested
specimens.
Abstract: A systems approach model for prostate cancer in prostate duct, as a sub-system of the organism is developed. It is accomplished in two steps. First this research work starts with a nonlinear system of coupled Fokker-Plank equations which models continuous process of the system like motion of cells. Then extended to PDEs that include discontinuous processes like cell mutations, proliferation and deaths. The discontinuous processes is modeled by using intensity poisson processes. The model incorporates the features of the prostate duct. The system of PDEs spatial coordinate is along the proximal distal axis. Its parameters depend on features of the prostate duct. The movement of cells is biased towards distal region and mutations of prostate cancer cells is localized in the proximal region. Numerical solutions of the full system of equations are provided, and are exhibit traveling wave fronts phenomena. This motivates the use of the standard transformation to derive a canonically related system of ODEs for traveling wave solutions. The results obtained show persistence of prostate cancer by showing that the non-negative cone for the traveling wave system is time invariant. The traveling waves have a unique global attractor is proved also. Biologically, the global attractor verifies that evolution of prostate cancer stem cells exhibit the avascular tumor growth. These numerical solutions show that altering prostate stem cell movement or mutation of prostate cancer cells lead to avascular tumor. Conclusion with comments on clinical implications of the model is discussed.
Abstract: This paper presents a technical speaker adaptation
method called WMLLR, which is based on maximum likelihood linear
regression (MLLR). In MLLR, a linear regression-based transform
which adapted the HMM mean vectors was calculated to maximize the
likelihood of adaptation data. In this paper, the prior knowledge of the
initial model is adequately incorporated into the adaptation. A series of
speaker adaptation experiments are carried out at a 30 famous city
names database to investigate the efficiency of the proposed method.
Experimental results show that the WMLLR method outperforms the
conventional MLLR method, especially when only few utterances
from a new speaker are available for adaptation.
Abstract: Current image-based individual human recognition
methods, such as fingerprints, face, or iris biometric modalities
generally require a cooperative subject, views from certain aspects,
and physical contact or close proximity. These methods cannot
reliably recognize non-cooperating individuals at a distance in the
real world under changing environmental conditions. Gait, which
concerns recognizing individuals by the way they walk, is a relatively
new biometric without these disadvantages. The inherent gait
characteristic of an individual makes it irreplaceable and useful in
visual surveillance.
In this paper, an efficient gait recognition system for human
identification by extracting two features namely width vector of
the binary silhouette and the MPEG-7-based region-based shape
descriptors is proposed. In the proposed method, foreground objects
i.e., human and other moving objects are extracted by estimating
background information by a Gaussian Mixture Model (GMM) and
subsequently, median filtering operation is performed for removing
noises in the background subtracted image. A moving target classification
algorithm is used to separate human being (i.e., pedestrian)
from other foreground objects (viz., vehicles). Shape and boundary
information is used in the moving target classification algorithm.
Subsequently, width vector of the outer contour of binary silhouette
and the MPEG-7 Angular Radial Transform coefficients are taken as
the feature vector. Next, the Principal Component Analysis (PCA)
is applied to the selected feature vector to reduce its dimensionality.
These extracted feature vectors are used to train an Hidden Markov
Model (HMM) for identification of some individuals. The proposed
system is evaluated using some gait sequences and the experimental
results show the efficacy of the proposed algorithm.
Abstract: The topic of surface flattening plays a vital role in the field of computer aided design and manufacture. Surface flattening enables the production of 2D patterns and it can be used in design and manufacturing for developing a 3D surface to a 2D platform, especially in fashion design. This study describes surface flattening based on minimum energy methods according to the property of different fabrics. Firstly, through the geometric feature of a 3D surface, the less transformed area can be flattened on a 2D platform by geodesic. Then, strain energy that has accumulated in mesh can be stably released by an approximate implicit method and revised error function. In some cases, cutting mesh to further release the energy is a common way to fix the situation and enhance the accuracy of the surface flattening, and this makes the obtained 2D pattern naturally generate significant cracks. When this methodology is applied to a 3D mannequin constructed with feature lines, it enhances the level of computer-aided fashion design. Besides, when different fabrics are applied to fashion design, it is necessary to revise the shape of a 2D pattern according to the properties of the fabric. With this model, the outline of 2D patterns can be revised by distributing the strain energy with different results according to different fabric properties. Finally, this research uses some common design cases to illustrate and verify the feasibility of this methodology.
Abstract: PPX(Pretty Printer for XML) is a query language that offers a concise description method of formatting the XML data into HTML. In this paper, we propose a simple specification of formatting method that is a combination description of automatic layout operators and variables in the layout expression of the GENERATE clause of PPX. This method can automatically format irregular XML data included in a part of XML with layout decision rule that is referred to DTD. In the experiment, a quick comparison shows that PPX requires far less description compared to XSLT or XQuery programs doing same tasks.
Abstract: This article outlines conceptualization and
implementation of an intelligent system capable of extracting
knowledge from databases. Use of hybridized features of both the
Rough and Fuzzy Set theory render the developed system flexibility
in dealing with discreet as well as continuous datasets. A raw data set
provided to the system, is initially transformed in a computer legible
format followed by pruning of the data set. The refined data set is
then processed through various Rough Set operators which enable
discovery of parameter relationships and interdependencies. The
discovered knowledge is automatically transformed into a rule base
expressed in Fuzzy terms. Two exemplary cancer repository datasets
(for Breast and Lung Cancer) have been used to test and implement
the proposed framework.
Abstract: In this investigation, types of commercial and special
polyacrylonitrile (PAN) fibers contain sodium 2-methyl-2-
acrylamidopropane sulfonate (SAMPS) and itaconic acid (IA)
comonomers were studied by fourier transform infrared (FT-IR)
spectroscopy. The study of FT-IR spectra of PAN fibers samples
with different comonomers shows that during stabilization of PAN
fibers, the peaks related to C≡N bonds and CH2 are reduced sharply.
These reductions are related to cyclization of nitrile groups and
stabilization procedure. This reduction in PAN fibers contain IA
comonomer is very intense in comparison with PAN fibers contain
SAMPS comonomer. This fact indicates the cycling and stabilization
for sample contain IA comonomer have been conducted more
completely. Therefore the carbon fibers produced from this material
have higher tensile strength due to suitable stabilization.
Abstract: The aim of this paper is to present a new method
which can be used for progressive transmission of electrocardiogram
(ECG). The idea consists in transforming any ECG signal to an
image, containing one beat in each row. In the first step, the beats are
synchronized in order to reduce the high frequencies due to inter-beat
transitions. The obtained image is then transformed using a discrete
version of Radon Transform (DRT). Hence, transmitting the ECG,
leads to transmit the most significant energy of the transformed
image in Radon domain. For decoding purpose, the receptor needs to
use the inverse Radon Transform as well as the two synchronization
frames.
The presented protocol can be adapted for lossy to lossless
compression systems. In lossy mode we show that the compression
ratio can be multiplied by an average factor of 2 for an acceptable
quality of reconstructed signal. These results have been obtained on
real signals from MIT database.
Abstract: This paper evaluates performances of an adaptive noise
cancelling (ANC) based target detection algorithm on a set of real test
data supported by the Defense Evaluation Research Agency (DERA
UK) for multi-target wideband active sonar echolocation system. The
hybrid algorithm proposed is a combination of an adaptive ANC
neuro-fuzzy scheme in the first instance and followed by an iterative
optimum target motion estimation (TME) scheme. The neuro-fuzzy
scheme is based on the adaptive noise cancelling concept with the
core processor of ANFIS (adaptive neuro-fuzzy inference system) to
provide an effective fine tuned signal. The resultant output is then
sent as an input to the optimum TME scheme composed of twogauge
trimmed-mean (TM) levelization, discrete wavelet denoising
(WDeN), and optimal continuous wavelet transform (CWT) for
further denosing and targets identification. Its aim is to recover the
contact signals in an effective and efficient manner and then determine
the Doppler motion (radial range, velocity and acceleration) at very
low signal-to-noise ratio (SNR). Quantitative results have shown that
the hybrid algorithm have excellent performance in predicting targets-
Doppler motion within various target strength with the maximum
false detection of 1.5%.
Abstract: Recently, a quality of motors is inspected by human
ears. In this paper, I propose two systems using a method of speech
recognition for automation of the inspection. The first system is based
on a method of linear processing which uses K-means and Nearest
Neighbor method, and the second is based on a method of non-linear
processing which uses neural networks. I used motor sounds in these
systems, and I successfully recognize 86.67% of motor sounds in the
linear processing system and 97.78% in the non-linear processing
system.
Abstract: Business transformation initiatives are required by
any organization to jump from its normal mode of operation to the
one that is suitable for the change in the environment such as
competitive pressures, regulatory requirements, changes in labor
market, etc., or internal such as changes in strategy/vision, changes in
the capability, change in the management, etc. Recent advances in
information technology in automating the business processes have
the potential to transform an organization to provide it with a
sustained competitive advantage. Process constitutes the skeleton of
a business. Thus, for a business to exist and compete well, it is
essential for the skeleton to be robust and agile. This paper details
“transformation" from a business perspective, methodologies to bring
about an effective transformation, process-based transformation, and
the role of services computing in this. Further, it details the benefits
that could be achieved through services computing.
Abstract: The purpose of this study was to evaluate and
compare new indices based on the discrete wavelet transform
with another spectral parameters proposed in the literature as
mean average voltage, median frequency and ratios between
spectral moments applied to estimate acute exercise-induced
changes in power output, i.e., to assess peripheral muscle
fatigue during a dynamic fatiguing protocol. 15 trained
subjects performed 5 sets consisting of 10 leg press, with 2
minutes rest between sets. Surface electromyography was
recorded from vastus medialis (VM) muscle. Several surface
electromyographic parameters were compared to detect
peripheral muscle fatigue. These were: mean average voltage
(MAV), median spectral frequency (Fmed), Dimitrov spectral
index of muscle fatigue (FInsm5), as well as other five
parameters obtained from the discrete wavelet transform
(DWT) as ratios between different scales. The new wavelet
indices achieved the best results in Pearson correlation
coefficients with power output changes during acute dynamic
contractions. Their regressions were significantly different
from MAV and Fmed. On the other hand, they showed the
highest robustness in presence of additive white gaussian
noise for different signal to noise ratios (SNRs). Therefore,
peripheral impairments assessed by sEMG wavelet indices
may be a relevant factor involved in the loss of power output
after dynamic high-loading fatiguing task.
Abstract: In this article, a method has been offered to classify
normal and defective tiles using wavelet transform and artificial
neural networks. The proposed algorithm calculates max and min
medians as well as the standard deviation and average of detail
images obtained from wavelet filters, then comes by feature vectors
and attempts to classify the given tile using a Perceptron neural
network with a single hidden layer. In this study along with the
proposal of using median of optimum points as the basic feature and
its comparison with the rest of the statistical features in the wavelet
field, the relational advantages of Haar wavelet is investigated. This
method has been experimented on a number of various tile designs
and in average, it has been valid for over 90% of the cases. Amongst
the other advantages, high speed and low calculating load are
prominent.
Abstract: Web usage mining has become a popular research
area, as a huge amount of data is available online. These data can be
used for several purposes, such as web personalization, web structure
enhancement, web navigation prediction etc. However, the raw log
files are not directly usable; they have to be preprocessed in order to
transform them into a suitable format for different data mining tasks.
One of the key issues in the preprocessing phase is to identify web
users. Identifying users based on web log files is not a
straightforward problem, thus various methods have been developed.
There are several difficulties that have to be overcome, such as client
side caching, changing and shared IP addresses and so on. This paper
presents three different methods for identifying web users. Two of
them are the most commonly used methods in web log mining
systems, whereas the third on is our novel approach that uses a
complex cookie-based method to identify web users. Furthermore we
also take steps towards identifying the individuals behind the
impersonal web users. To demonstrate the efficiency of the new
method we developed an implementation called Web Activity
Tracking (WAT) system that aims at a more precise distinction of
web users based on log data. We present some statistical analysis
created by the WAT on real data about the behavior of the Hungarian
web users and a comprehensive analysis and comparison of the three
methods
Abstract: Arc welding creates a weld pool to realize continuity between pieces of assembly. The thermal history of the weld is dependent on heat transfer and fluid flow in the weld pool. The metallurgical transformation during welding and cooling are modeled in the literature only at solid state neglecting the fluid flow. In the present paper we associate a heat transfer – fluid flow and metallurgical model for the 16MnD5 steel. The metallurgical transformation model is based on Leblond model for the diffusion kinetics and on the Koistinen-Marburger equation for Marteniste transformation. The predicted thermal history and metallurgical transformations are compared to a simulation without fluid phase. This comparison shows the great importance of the fluid flow modeling.
Abstract: The study explored the question of who am I? As a (re)construction of cultural identity by delving into globalization, communication, and social change in Malta during a historical moment when Malta became a European Union Member State. Three objectives guided this qualitative study. Firstly the study reviewed European Union (EU) policies that regulate broadcasting and their implementation in Member States, whilst meeting the challenges of globalization and new media technology. Secondly the research investigated the changes of the media landscape via organizational structures, programs and television (TV) content. Finally the study explored the impact of these transformations taking place in the way Maltese live as they (re)construct their cultural identity. Despite the choices available to the Maltese audience, old local traditions and new foreign customs coexist as informants continue to (re)construct their cultural identity and define who they are.
Abstract: A concrete structure is designed and constructed for its
purpose of use, and is expected to maintain its function for the target
durable years from when it was planned. Nevertheless, as time elapses
the structure gradually deteriorates and then eventually degrades to the
point where the structure cannot exert the function for which it was
planned. The performance of concrete that is able to maintain the level
of the performance required over the designed period of use as it has
less deterioration caused by the elapse of time under the designed
condition is referred to as Durability. There are a number of causes of
durability degradation, but especially chloride damage, carbonation,
freeze-thaw, etc are the main causes. In this study, carbonation, one of
the main causes of deterioration of the durability of a concrete
structure, was investigated via a microstructure analysis technique.
The method for the measurement of carbonation was studied using the
existing indicator method, and the method of measuring the progress
of carbonation in a quantitative manner was simultaneously studied
using a FT-IR (Fourier-Transform Infrared) Spectrometer along with
the microstructure analysis technique.
Abstract: The paper presents a technique suitable in robot
vision applications where it is not possible to establish the object position from one view. Usually, one view pose calculation methods
are based on the correspondence of image features established at a
training step and exactly the same image features extracted at the
execution step, for a different object pose. When such a
correspondence is not feasible because of the lack of specific features
a new method is proposed. In the first step the method computes
from two views the 3D pose of feature points. Subsequently, using a
registration algorithm, the set of 3D feature points extracted at the execution phase is aligned with the set of 3D feature points extracted
at the training phase. The result is a Euclidean transform which have
to be used by robot head for reorientation at execution step.